Triple

T36571795
Position Surface form Disambiguated ID Type / Status
Subject Richmond E902138 entity
Predicate moralAlignmentInPlay P22459 FINISHED
Object virtuous LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: virtuous | Statement: [Richmond, moralAlignmentInPlay, virtuous]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: moralAlignmentInPlay
Context triple: [Richmond, moralAlignmentInPlay, virtuous]
  • A. characterAlignment chosen
    Indicates the moral or ethical stance a character holds, typically along axes such as good–evil and lawful–chaotic.
  • B. hasMoralArchetype
    Indicates that an entity exemplifies or is characterized by a particular moral pattern, role, or ethical archetype.
  • C. hasMoralStrategy
    Indicates that an entity employs or follows a particular approach or set of principles for making moral or ethical decisions.
  • D. isMoralFoilFor
    Indicates that one entity serves as a contrasting counterpart whose differing moral qualities highlight or emphasize the moral traits of another entity.
  • E. hasMoralComplexity
    Indicates that the relationship or action involves nuanced ethical considerations, conflicting values, or ambiguity in determining what is morally right or wrong.
  • F. None of above.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f76e6416708190a9754b8c52d4e453 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c777e924819081a6634f549fe552 completed May 3, 2026, 10:08 p.m.
PD Predicate disambiguation batch_69f7c477a4d481908f52e55b6688f60c completed May 3, 2026, 9:56 p.m.
Created at: May 3, 2026, 4:11 p.m.